Operations | Monitoring | ITSM | DevOps | Cloud

3 ways to drive software delivery success with Datadog DORA Metrics

Delivering software quickly and reliably is the main focus of modern DevOps. But to improve your delivery performance, you need to understand it, and that starts with measurement. Teams primarily measure performance in this area by using DORA metrics—deployment frequency, change lead time, change failure rate, and time to restore service*. These metrics help teams understand trends in their software delivery practices in quantifiable terms that they can track and improve over time.

The Datadog Agent: Why it's essential for monitoring your infrastructure and applications with Datadog

If you’re a Datadog customer, you’re likely using our platform to gain visibility into your infrastructure and applications and to troubleshoot using logs, metrics, and traces when issues arise. To support these efforts, you’ll want access to the most granular telemetry signals and intuitive workflows that streamline your investigation.

AWS Lambda's INIT billing update: What's changing and why it matters for your cloud costs

Starting on Aug. 1, 2025, AWS will bill for the initialization (INIT) phase of Lambda functions, bringing a key change to how you are charged for serverless workloads. This billing update will impact functions using managed runtimes with ZIP archive packaging, which previously excluded the INIT phase from the billed duration. For teams that rely heavily on AWS Lambda, this is a small but significant change. The INIT phase, while short, could introduce costs that were previously invisible.

Stop Guessing, Start Measuring: Optimizing Rancher Continuous Delivery With Fleet Benchmarks

Rancher Continuous Delivery (known as Fleet) can be used in a workflow to deploy applications to many clusters. With its GitOps support, it enables downstream clusters to pull updates from a Git repository. We know of users that monitor several hundred Git repositories and deploy to a thousand clusters. To make this scale possible, several intermediate steps are necessary. First, the application is converted into separate bundles, which are then targeted at clusters.

State of the Observability Databases with Dee Kitchen (Grafana Office Hours #30)

In this Grafana Office Hours, we talk about the state of observability databases (Grafana Loki, Mimir, Tempo, and Pyroscope) and where they're going. We talk about current and upcoming architectural changes in all four, how we're making them more performant, how compatible they are with OpenTelemetry, and what we're working on next for each database. In this conversation are Dee Kitchen (VP of Engineering for Databases) and Senior Developer Advocates Jay Clifford and Nicole van der Hoeven.

Debugging Microservices

Debugging microservices is tough, especially when you're juggling multiple services and relying only on logs. This video cuts through the complexity by showing you how to implement distributed tracing using Sentry. You'll see a practical demonstration in a food ordering app (built with React and Go) of how tracing can give you a clear view of your entire request flow, from the initial button click to the final operation across all your services.